New approach for simultaneous spectral analysis of a complex mixture using the fractional wavelet transform

Dinç, Erdal; Demirkaya, Fatma; Băleanu, Dumitru; Kadıoğlu, Yücel; Kadıoğlu, Ekrem

doi:10.1016/j.cnsns.2009.05.021

Cited by 24 publications

(11 citation statements)

References 9 publications

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“…To overcome the above mentioned drawbacks of the mentioned classical signal processing methods, the CWT method has been successfully used for the quantitative resolution of multicomponent mixtures without using any priori separation procedure. Very recently a new and powerful method called the fractional wavelet transform (FWT) was introduced in [10][11][12][13], and applied successfully to the quantitative analysis of the drug complex mixtures possessing overlapping spectra [14,15]. One way to improve the obtained results for these kind of spectra is to think to apply two or more methods one after each other.…”

Section: Introductionmentioning

confidence: 99%

Fractional and continuous wavelet transforms for the simultaneous spectral analysis of a binary mixture system

Dinç

Büker

Băleanu

2011

Communications in Nonlinear Science and Numerical Simulation

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Section: Introductionmentioning

confidence: 99%

Fractional and continuous wavelet transforms for the simultaneous spectral analysis of a binary mixture system

Dinç

Büker

Băleanu

2011

Communications in Nonlinear Science and Numerical Simulation

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“…It can be combined with principal component regression where the partial least squares calibrations are performed for quantitative analysis. The absorption spectra are processed by fractional wavelet transform [12][13].…”

Section: Introductionmentioning

confidence: 99%

Comparative study of noise reduction approaches with engineering applications in time domain and frequency domain

Ye¹,

Mohamadian²

2012

2012 7th International Conference on Computer Science &Amp; Education (ICCSE)

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Noise effects are unavoidable in engineering data acquisition systems. Noise reduction is necessary for numerous practical problems in either time domain or frequency domain, where measurements and observations are contaminated by diverse sources of noise. Advanced noise reduction algorithms should be applied to minimize the impact of data corruption in problem solving. Thus, a comparative study is made on a basis of several denoising methods, such as the adaptive recursive least square (RLS) filter, multi-layer neural network training via backpropagation algorithm and discrete wavelet denoising. Two case studies are conducted: the laser Doppler spectral filtering in frequency domain and rapid compression machine pressure profile signal denoising in time domain, in order to evaluate these typical noise removal approaches.

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“…It has the ability of showing local features of the signal both in the time domain and frequency domain. With the multiresolution analysis of wavelet transform, noise can be suppressed in large scale, and the precise positioning of the edge can be achieved in small scale [2].…”

Section: Edge Detection Based On Wavelet Transformmentioning

confidence: 99%

“…Obviously, the local maximum point of module 2 A f x y shows the direction of gradient. The choice of scale s is very important in multi-scale edge detection [3].…”

Section: The Principle Of Wavelet Transformmentioning

confidence: 99%

A contour extraction algorithm based on wavelet transform and dynamic contour compensation

Mu¹,

Shuai²,

Ma³

2017

Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 20

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Contour extraction process is often disturbed by complex backgrounds or foregrounds in the machine vision system. A new contour extraction algorithm is proposed based on wavelet transform and dynamic contour compensation. The wavelet transform method is used to extract the edge of image, and the dynamic compensation is used to restore the contour which is affected by the complex dark areas such as bar code or black icon. The algorithm is applied in a sausage machine vision inspection system, and it is proved effective in eliminating the contour depression and retaining the actual defect features.

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New approach for simultaneous spectral analysis of a complex mixture using the fractional wavelet transform

Cited by 24 publications

References 9 publications

Fractional and continuous wavelet transforms for the simultaneous spectral analysis of a binary mixture system

Fractional and continuous wavelet transforms for the simultaneous spectral analysis of a binary mixture system

Comparative study of noise reduction approaches with engineering applications in time domain and frequency domain

A contour extraction algorithm based on wavelet transform and dynamic contour compensation

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